Just as every human genome is unique, so too is the community of microbial populations that reside within and on the human body. This dynamic community - the microbiome - complements the human genome to maintain health by synthesizing vitamins, assisting in digestion, educating the immune system, and providing colonization resistance to pathogens. Although it is widely accepted that this microbial community is critical to maintaining health and that disturbances to the community induced through antibiotics or stress can facilitate disease, there is a general lack of understanding with regards to the ecological principles and specific mechanisms that shape host-associated communities. Toward this goal it is critical to develop a quantitative framework for describing the role of biodiversity in shaping and maintaining the stability of host-associated communities. The objective of this proposal is to evaluate and model the relationships between the diversity of the microbiota and its stability in host-associated microbial communities. The central hypothesis for the proposed research is that increased diversity within the gut microbiome will result in greater community-level stability, but less population-level stability. The rationale for this hypothesis comes from observations in the field of landscape ecology that variation in total plant biomass production is reduced in high diversity ecosystems, but the variation in biomass of individual plant populations is not stabilized by diversity. This hypothesis will be tested by generating mouse-associated microbial communities with varying levels of diversity that will be used to assess and mathematically model changes in the gut community using a combination of 16S rRNA and random sequencing approaches. The specific aims of the proposed research are to 1) model the normal mouse-associated microbial community; 2) measure the effects of taxonomic diversity on stability; and 3) assess the effects of functional diversity on stability. Te combination of ecological and mathematical tools will provide a strong theoretical basis to understand the dynamics of host-associated microbial communities. These innovative studies will assess the level of variation between individual mice where factors such as genetics, diet, environment, age, and sex are controlled. The proposed research will have a significant impact on our understanding of host-associated microbial communities because for the first time, we will be able to measure and model the normal variation in the composition and function of the microbiome. Furthermore, the principles and ecological modeling that is pursued in the proposed research will impact our understanding of health and disease in humans.